geosql 0.9.0

Install GeoSQL instructions into local AI CLIs.

geosql

Claude/Codex geospatial SQL skill for data scientists and analysts working with geospatial data on BigQuery and Snowflake.

Describe what you want geographically, and skill writes and runs SQL against free map datasets (Overture Maps) in BigQuery or Snowflake, checks the cost, validates the answer, and (if you ask) shows you the map — without surprise bills or hand-waved results.

Example questions it handles well:

• "Show me all bike lanes in Amsterdam"
• "How many buildings are in downtown Tokyo?"
• "Map the rail network in Germany"
• "Aggregate restaurant density in NYC by H3 cell"

It works with any private GEOGRAPHY/GEOMETRY dataset too.

Install (Claude/Codex)

Prerequisites

• bq or snow CLI installed and authenticated with default project/connection (!) configured.

Install SKILL

In Claude Code (recommended):

/plugin marketplace add dekart-xyz/geosql
/plugin install geosql

With Python (interactive mode):

pip install geosql
geosql

With Node.js:

npx skills add dekart-xyz/geosql

Then type /geosql in your agent's prompt to use the skill.

Enable map rendering (recommended)

pip install dekart
dekart init

Feature List

🗺️ Data discovery

• Auto-explores warehouse metadata (tables, columns, types) instead of guessing.
• Works with BigQuery (bigquery-public-data.overture_maps) and Snowflake (OVERTURE_MAPS__* marketplace shares).

💸 Cost safety

• Always dry-runs BigQuery queries first to estimate bytes scanned.
• Enforces a 10 GiB billing cap by default (--maximum_bytes_billed).
• Refuses to execute over-budget queries — rewrites them cheaper instead (tighter bbox, lower H3 resolution, more filters).
• Uses the bbox overlap pattern (not containment) for fast partition pruning, then ST_INTERSECTS for geographic correctness.

✅ Mandatory validation

Before showing you a final query, it:

1. Dry-runs for cost.
2. Runs COUNT(*) to confirm rows exist and are reasonable.
3. Computes total area (polygons) or total length (lines) as a sanity check.
4. Cross-checks numbers against domain knowledge — debugs if something looks off.

🔷 H3 spatial aggregation

• Built-in support for hexagonal grid rollups (heatmaps, density).
• Region-aware namespaces (jslibs.h3.* for US, jslibs.eu_h3.* for EU).
• Cost rules: filter first, aggregate before adding heavy boundary geometry.

🗺️ Map rendering

• Uses the dekart CLI to turn results into an interactive map.
• Workflow: create report → dataset → upload CSV → snapshot → inspect.
• Only triggers when you explicitly say "map" — never auto-renders.
• Smart styling rules: picks layer type by question (Points for positions, H3 for density, Arcs for origin-destination, etc.), uses appropriate palettes, locks zoom to the insight.